ResPCANet

A repository for the code used to create and train the model defined in "PCANet Combined with Residual Connection for Hyperspectral Image Classification". https://ieeexplore.ieee.org/document/9980165

2023.02.21

I have submitted the comparison method, PCANet(2014) in the paper. This model is mainly based on the implementation of pytorch and python3. My model code is improved on this basis. You can modify the code slightly to complete the implementation of the code. If you have questions, you can leave a message.

Citation

If you want to directly reference the method of PCANet, please directly reference the information of the work.

@ARTICLE{7234886,
  author={Chan, Tsung-Han and Jia, Kui and Gao, Shenghua and Lu, Jiwen and Zeng, Zinan and Ma, Yi},
  journal={IEEE Transactions on Image Processing}, 
  title={PCANet: A Simple Deep Learning Baseline for Image Classification?}, 
  year={2015},
  volume={24},
  number={12},
  pages={5017-5032},
  doi={10.1109/TIP.2015.2475625}}

The methods quoted in our paper are as follows.

@INPROCEEDINGS{9980165,
  author={Li, Mianpeng and Xu, Xiang},
  booktitle={2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)}, 
  title={PCANet Combined with Residual Connection for Hyperspectral Image Classification}, 
  year={2022},
  volume={},
  number={},
  pages={1-7},
  doi={10.1109/CISP-BMEI56279.2022.9980165}}

building